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    User reports Apodex 1.1 handled a CSV analysis from planning to report

    In a post made in collaboration with the Apodex team, a user says the model let them intervene mid-task while preserving valid intermediate results and replanning only affected steps.

    SA
    1 Source, 19d ago, first seen 19d ago

    TLDR

    A user who says they struggled to keep Codex on track for data analysis describes trying Apodex 1.1 after its team reached out. They report that it inspected their dataset, planned an analysis, wrote Python to clean and transform the data, executed the scripts and produced a report answering their question—all in one long-running task. The user also says they could intervene without restarting the task. They disclosed collaborating with the Apodex team on the post.

    Combined views

    19K

    1 Source, first seen 19d ago

    Combined views

    19K

    1 Source, first seen 19d ago

    74 likes
    74 likes
    31 comments
    69 saves
    3 reposts

    Sentiment

    Positive——Negative

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    31 comments
    69 saves
    3 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    1 Source

    @svpinoI've been trying Codex to analyze a dataset, and honestly, I've gotten nowhere. Generating a nice-looking report about the data isn't enough. For this to be useful, Codex needs to inspect tables, clean existing data, choose the correct statistical methods, run the analysis, and support its conclusions with evidence. There are too many tasks to coordinate, and it's taking me a long time to write a skill with the complete workflow so I can keep Codex on task. The Apodex team reached out to me to show me their Apodex 1.1 model. It includes an open-source framework and an open-weight version of the model. I uploaded a CSV file and asked a question that I couldn't answer by simply summarizing the table. Apodex created an analysis plan, wrote the code, and executed it inside a single long-running task: 1. It inspected the tables 2. It determined the steps to answer the question 3. It wrote Python code to clean and transform the dataset 4. It executed the scripts in its environment 5. It generated a final report with the answer This is what Apodex calls Environment Scaling. I could intervene while a task was running, and the system preserved all intermediate results that remained valid and replanned only the affected parts instead of restarting the task. Apodex 1.1 takes reasoning out of the report and puts it into executing real tasks. Thanks to the team for collaborating with me on this post. GitHub links below:

    1 Source

    @svpinoI've been trying Codex to analyze a dataset, and honestly, I've gotten nowhere. Generating a nice-looking report about the data isn't enough. For this to be useful, Codex needs to inspect tables, clean existing data, choose the correct statistical methods, run the analysis, and support its conclusions with evidence. There are too many tasks to coordinate, and it's taking me a long time to write a skill with the complete workflow so I can keep Codex on task. The Apodex team reached out to me to show me their Apodex 1.1 model. It includes an open-source framework and an open-weight version of the model. I uploaded a CSV file and asked a question that I couldn't answer by simply summarizing the table. Apodex created an analysis plan, wrote the code, and executed it inside a single long-running task: 1. It inspected the tables 2. It determined the steps to answer the question 3. It wrote Python code to clean and transform the dataset 4. It executed the scripts in its environment 5. It generated a final report with the answer This is what Apodex calls Environment Scaling. I could intervene while a task was running, and the system preserved all intermediate results that remained valid and replanned only the affected parts instead of restarting the task. Apodex 1.1 takes reasoning out of the report and puts it into executing real tasks. Thanks to the team for collaborating with me on this post. GitHub links below: